Atherosclerosis evaluation and cardiovascular risk estimation using coronary computed tomography angiography.

Clinical risk scores based on traditional risk factors of atherosclerosis correlate imprecisely to an individual's complex pathophysiological predisposition to atherosclerosis and provide limited accuracy for predicting major adverse cardiovascular events (MACE). Over the past two decades, computed tomography scanners and techniques for coronary computed tomography angiography (CCTA) analysis have substantially improved, enabling more precise atherosclerotic plaque quantification and characterization. The accuracy of CCTA for quantifying stenosis and atherosclerosis has been validated in numerous multicentre studies and has shown consistent incremental prognostic value for MACE over the clinical risk spectrum in different populations. Serial CCTA studies have advanced our understanding of vascular biology and atherosclerotic disease progression. The direct disease visualization of CCTA has the potential to be used synergistically with indirect markers of risk to significantly improve prevention of MACE, pending large-scale randomized evaluation.

Progression of non-obstructive coronary plaque: a practical CCTA-based risk score from the PARADIGM registry.

OBJECTIVES: No clear recommendations are endorsed by the different scientific societies on the clinical use of repeat coronary computed tomography angiography (CCTA) in patients with non-obstructive coronary artery disease (CAD). This study aimed to develop and validate a practical CCTA risk score to predict medium-term disease progression in patients at a low-to-intermediate probability of CAD. METHODS: Patients were part of the Progression of AtheRosclerotic PlAque Determined by Computed Tomographic Angiography Imaging (PARADIGM) registry. Specifically, 370 (derivation cohort) and 219 (validation cohort) patients with two repeat, clinically indicated CCTA scans, non-obstructive CAD, and absence of high-risk plaque (≥ 2 high-risk features) at baseline CCTA were included. Disease progression was defined as the new occurrence of ≥ 50% stenosis and/or high-risk plaque at follow-up CCTA. RESULTS: In the derivation cohort, 104 (28%) patients experienced disease progression. The median time interval between the two CCTAs was 3.3 years (2.7-4.8). Odds ratios for disease progression derived from multivariable logistic regression were as follows: 4.59 (95% confidence interval: 1.69-12.48) for the number of plaques with spotty calcification, 3.73 (1.46-9.52) for the number of plaques with low attenuation component, 2.71 (1.62-4.50) for 25-49% stenosis severity, 1.47 (1.17-1.84) for the number of bifurcation plaques, and 1.21 (1.02-1.42) for the time between the two CCTAs. The C-statistics of the model were 0.732 (0.676-0.788) and 0.668 (0.583-0.752) in the derivation and validation cohorts, respectively. CONCLUSIONS: The new CCTA-based risk score is a simple and practical tool that can predict mid-term CAD progression in patients with known non-obstructive CAD. CLINICAL RELEVANCE STATEMENT: The clinical implementation of this new CCTA-based risk score can help promote the management of patients with non-obstructive coronary disease in terms of timing of imaging follow-up and therapeutic strategies. KEY POINTS: • No recommendations are available on the use of repeat CCTA in patients with non-obstructive CAD. • This new CCTA score predicts mid-term CAD progression in patients with non-obstructive stenosis at baseline. • This new CCTA score can help guide the clinical management of patients with non-obstructive CAD.

Incorporating coronary artery calcium scoring in the prediction of obstructive coronary artery disease with myocardial ischemia: a study with sequential use of coronary computed tomography angiography and positron emission tomography imaging.

BACKGROUND: Additional strategies are needed to refine the referral for diagnostic testing of symptomatic patients with suspected coronary artery disease (CAD). We aimed to compare various models to predict hemodynamically obstructive CAD. METHODS AND RESULTS: Symptomatic patients with suspected CAD who underwent coronary artery calcium scoring (CACS) and sequential coronary computed tomography angiography (CCTA) and [15O]H2O positron emission tomography (PET) myocardial perfusion imaging were analyzed. Obstructive CAD was defined as a suspected coronary artery stenosis on CCTA with myocardial ischemia on PET (absolute stress myocardial perfusion ≤ 2.4 mL/g/min in ≥ 1 segment). Three models were developed to predict obstructive CAD-induced myocardial ischemia using logistic regression analysis: (1) basic model: including age, sex and cardiac symptoms, (2) risk factor model: adding number of risk factors to the basic model, and (3) CACS model: adding CACS to the risk factor model. Model performance was evaluated using discriminatory ability with area under the receiver-operating characteristic curves (AUC). A total of 647 patients (mean age 62 ± 9 years, 45% men) underwent CACS and sequential CCTA and PET myocardial perfusion imaging. Obstructive CAD with myocardial ischemia on PET was present in 151 (23%) patients. CACS was independently associated with myocardial ischemia (P < .001). AUC for the discrimination of ischemia for the CACS model was superior over the basic model and risk factor model (P < .001). CONCLUSIONS: Adding CACS to the model including age, sex, cardiac symptoms and number of risk factors increases the accuracy to predict obstructive CAD with myocardial ischemia on PET in symptomatic patients with suspected CAD.

Association between left atrial epicardial fat, left atrial volume, and the severity of atrial fibrillation.

AIMS: Left atrial (LA) volume and LA epicardial fat are both substrates for atrial fibrillation (AF), but may relate with AF at different (early vs. late) stages in the AF disease process. We evaluated associations between LA epicardial fat and LA volume in patients with sinus rhythm (SR), paroxysmal AF (PAF), and persistent/permanent AF. METHODS AND RESULTS: In total, 300 patients (100 with SR, 100 with PAF, and 100 with persistent/permanent AF) who underwent cardiac computed tomography angiography (CTA) were included. The epicardial fat mass posterior to the LA and the LA volume were quantified from CTA and compared between patients with SR, PAF, and persistent/permanent AF. Furthermore, four groups were created by classifying LA epicardial fat and LA volume into large or small according to their median. The mean age of the population was 58.9 ± 10.5 years and 69.7% was male. Left atrial epicardial fat mass was larger in patients with PAF compared with SR, but did not further increase from PAF to persistent/permanent AF. Left atrial volume increased significantly from SR to PAF and to persistent/permanent AF. Left atrial epicardial fat and LA volume were both concordantly large or small in 184 (61%) patients, and discordant in 116 (39%). When both were small, 65.2% of the patients had SR, 23.9% PAF, and 10.9% persistent/permanent AF. When the LA epicardial fat mass was large and the LA volume small (compared with both being small), patients were significantly more often in PAF (55.2 vs. 23.9, P < 0.05), less frequently in SR (32.8% vs. 65.2%, P < 0.05) but showed comparable rates of persistent/permanent AF (12.0% vs. 10.9%, P < 0.05). When the LA volume was large, most patients had persistent/permanent AF. CONCLUSION: Left atrial epicardial fat mass was larger in PAF vs. SR, possibly indicating a marker of early disease, while large LA volumes were associated with a high prevalence of persistent/permanent AF. Elevated LA epicardial fat mass without large LA volume may reflect the early AF disease process.

Relationship between coronary artery calcification and myocardial ischemia on computed tomography myocardial perfusion in patients with stable chest pain.

BACKGROUND: Coronary artery calcium (CAC) score has shown to provide incremental prognostic information when added to the Framingham risk score. Although the relation between CAC and myocardial ischemia has been evaluated, there has been little evaluation of the relationship between CAC score and inducible myocardial ischemia on computed tomography myocardial perfusion (CTP). METHODS AND RESULTS: Patients who were referred with stable chest pain from the outpatient clinic and who underwent non-contrast computed tomography scan, coronary computed tomography angiography, and adenosine stress CTP were included in this study. CAC score was subdivided in four groups (1 to 99; 100 to 399, 400 to 999, and ≥ 1000). Inducible myocardial ischemia was considered when reversible perfusion defects were observed in ≥ 1 segment. A total of 131 patients (age 62 ± 9.4 years; 56% male) were included. The median CAC score was 241 (73 to 539). Forty-nine patients (37%) had evidence of inducible myocardial ischemia. The presence of inducible myocardial ischemia increased with increasing CAC score from 22% in the CAC score 1 to 99 subgroup to 35, 47, and 65% in the 100 to 399, 400 to 999, and ≥ 1000 CAC score subgroup, respectively. In multivariable analysis CAC score was the only determinant that significantly predicted the presence of inducible myocardial ischemia on CTP. CONCLUSIONS: In a population of symptomatic patients, the majority of patients with extensive calcification had evidence of inducible myocardial ischemia on CTP. CAC score was the only independent predictor of inducible myocardial ischemia on CTP.

Machine learning of clinical variables and coronary artery calcium scoring for the prediction of obstructive coronary artery disease on coronary computed tomography angiography: analysis from the CONFIRM registry.

AIMS: Symptom-based pretest probability scores that estimate the likelihood of obstructive coronary artery disease (CAD) in stable chest pain have moderate accuracy. We sought to develop a machine learning (ML) model, utilizing clinical factors and the coronary artery calcium score (CACS), to predict the presence of obstructive CAD on coronary computed tomography angiography (CCTA). METHODS AND RESULTS: The study screened 35 281 participants enrolled in the CONFIRM registry, who underwent ≥64 detector row CCTA evaluation because of either suspected or previously established CAD. A boosted ensemble algorithm (XGBoost) was used, with data split into a training set (80%) on which 10-fold cross-validation was done and a test set (20%). Performance was assessed of the (1) ML model (using 25 clinical and demographic features), (2) ML + CACS, (3) CAD consortium clinical score, (4) CAD consortium clinical score + CACS, and (5) updated Diamond-Forrester (UDF) score. The study population comprised of 13 054 patients, of whom 2380 (18.2%) had obstructive CAD (≥50% stenosis). Machine learning with CACS produced the best performance [area under the curve (AUC) of 0.881] compared with ML alone (AUC of 0.773), CAD consortium clinical score (AUC of 0.734), and with CACS (AUC of 0.866) and UDF (AUC of 0.682), P < 0.05 for all comparisons. CACS, age, and gender were the highest ranking features. CONCLUSION: A ML model incorporating clinical features in addition to CACS can accurately estimate the pretest likelihood of obstructive CAD on CCTA. In clinical practice, the utilization of such an approach could improve risk stratification and help guide downstream management.

Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging.

Artificial intelligence (AI) has transformed key aspects of human life. Machine learning (ML), which is a subset of AI wherein machines autonomously acquire information by extracting patterns from large databases, has been increasingly used within the medical community, and specifically within the domain of cardiovascular diseases. In this review, we present a brief overview of ML methodologies that are used for the construction of inferential and predictive data-driven models. We highlight several domains of ML application such as echocardiography, electrocardiography, and recently developed non-invasive imaging modalities such as coronary artery calcium scoring and coronary computed tomography angiography. We conclude by reviewing the limitations associated with contemporary application of ML algorithms within the cardiovascular disease field.

Computed tomography for planning transcatheter tricuspid valve therapy.

AIMS: Percutaneous transcatheter tricuspid valve therapy is an evolving treatment option for patients with significant tricuspid regurgitation (TR) deemed too fragile for open heart surgery. The present study proposes comprehensive anatomical evaluation of the tricuspid valve, right ventricle (RV), and vena cavae and its spatial relationships with the right coronary artery (RCA) using computed tomography (CT) and investigates the implications for suitability for current technologies. METHODS AND RESULTS: A total of 250 patients (mean age 80 ± 7.2 years, 52.4% men) undergoing CT were divided according to the presence of moderate or severe TR (≥3+, n = 40) and less than moderate TR (<3+, n = 210). Tricuspid valve annulus, RV, and vena cavae dimensions and the course of the RCA relative to the tricuspid annulus were evaluated. Patients with TR ≥ 3+ showed significantly larger dimensions of the tricuspid annulus, RV and vena cavae. In 64.8% of patients, the RCA coursed along the tricuspid valve annulus. Patients with TR <3+ showed more frequently a course of the RCA superior to the tricuspid annulus at the levels of the anterior and the posterior tricuspid leaflet compared with their counterparts (12.4% vs. 0%, P = 0.019). A less favourable course of the RCA (≤2.0 mm distance to the annulus) for current annuloplasty techniques was observed at the level of the anterior tricuspid and posterior leaflets in respective 12.5 and 27.5% of patients with TR ≥3+. CONCLUSION: The present study proposes a first systematic approach based on CT to define the patient suitability for current transcatheter tricuspid valve devices.

Relationship Between Coronary Contrast-Flow Quantitative Flow Ratio and Myocardial Ischemia Assessed by SPECT MPI.

PURPOSE: A new method has been developed to calculate fractional flow reserve (FFR) from invasive coronary angiography, the so-called "contrast-flow quantitative flow ratio (cQFR)". Recently, cQFR was compared to invasive FFR in intermediate coronary lesions showing an overall diagnostic accuracy of 85%. The purpose of this study was to investigate the relationship between cQFR and myocardial ischemia assessed by single-photon emission computed tomography myocardial perfusion imaging (SPECT MPI). METHODS: Patients who underwent SPECT MPI and coronary angiography within 3 months were included. The cQFR computation was performed offline, using dedicated software. The cQFR computation was based on 3-dimensional quantitative coronary angiography (QCA) and computational fluid dynamics. The standard 17-segment model was used to determine the vascular territories. Myocardial ischemia was defined as a summed difference score ≥2 in a vascular territory. A cQFR of ≤0.80 was considered abnormal. RESULTS: Two hundred and twenty-four coronary arteries were analysed in 85 patients. Overall accuracy of cQFR to detect ischemia on SPECT MPI was 90%. In multivariable analysis, cQFR was independently associated with ischemia on SPECT MPI (OR per 0.01 decrease of cQFR: 1.10; 95% CI 1.04-1.18, p = 0.002), whereas clinical and QCA parameters were not. Furthermore, cQFR showed incremental value for the detection of ischemia compared to clinical and QCA parameters (global chi square 48.7 to 62.6; p <0.001). CONCLUSIONS: A good relationship between cQFR and SPECT MPI was found. cQFR was independently associated with ischemia on SPECT MPI and showed incremental value to detect ischemia compared to clinical and QCA parameters.

Relation between quantitative coronary CTA and myocardial ischemia by adenosine stress myocardial CT perfusion.

BACKGROUND: Coronary-computed tomography angiography (CTA) has limited accuracy to predict myocardial ischemia. Besides luminal area stenosis, other coronary plaque morphology and composition parameters may help to assess ischemia. With the integration of coronary CTA and adenosine stress CT myocardial perfusion (CTP), reliable information regarding coronary anatomy and function can be derived in one procedure. This analysis aimed to investigate the association between coronary stenosis severity, plaque composition and morphology and the presence of ischemia measured with adenosine stress myocardial CTP. METHODS AND RESULTS: 84 patients (age, 62 ± 10 years; 48% men) who underwent sequential coronary CTA and adenosine stress myocardial CT perfusion were analyzed. Automated quantification was performed in all coronary lesions (quantitative CTA). Downstream myocardial ischemia was assessed by visual analysis of the rest and stress CTP images and defined as a summed difference score of ≥1. One or more coronary plaques were present in 146 coronary arteries of which 31 (21%) were ischemia-related. Of the lesions with a stenosis percentage <50%, 50%-70%, and >70%, respectively, 9% (6/67), 18% (9/51), and 57% (16/28) demonstrated downstream ischemia. Furthermore, mean plaque burden, plaque volume, lesion length, maximal plaque thickness, and dense calcium volume were significantly higher in ischemia-related lesions, but only stenosis severity (%) (OR 1.06; 95% CI 1.02-1.10; P = .006) and lesion length (mm) (OR 1.26; 95% CI 1.02-1.55; P = .029) were independent correlates. CONCLUSIONS: Increasing stenosis percentage by quantitative CTA is positively correlated to myocardial ischemia measured with adenosine stress myocardial CTP. However, stenosis percentage remains a moderate determinant. Lumen area stenosis and lesion length were independently associated with ischemia, adjusted for coronary plaque volume, mean plaque burden, maximal lesion thickness, and dense calcium volume.

Association of Left Atrial Appendage Morphology and Function With Stroke and Transient Ischemic Attack in Atrial Fibrillation Patients.

We aimed to correlate left atrial appendage (LAA) structure and function with the history of stroke/transient ischemic attack (TIA) in patients with atrial fibrillation (AF). We analyzed the data of 649 patients with AF who were scheduled for catheter ablation. Patients underwent cardiac computed tomography and transesophageal echocardiography before ablation. The LAA morphologies depicted by cardiac computed tomography were categorized into 4 groups: cauliflower, chicken wing, swan, and windsock shapes. The mean age was 61.3 ± 10.5 years, 33.9% were women. The prevalence of stroke/TIA was 7.1%. After adjustment for the main risk factors, the LAA flow velocity ≤35.3 cm/s (odds ratio [OR] 2.18, 95% confidence interval [CI] 1.09 to 4.61, p = 0.033) and the swan LAA shape (OR 2.69, 95% CI 0.96 to 6.86, p = 0.047) independently associated with a higher risk of stroke/TIA, whereas the windsock LAA morphology proved to be protective (OR 0.32, 95% CI 0.12 to 0.77, p = 0.017) compared with the cauliflower LAA shape. Comparing the differences between the LAA morphology groups, we measured a significantly smaller LAA orifice area (389.3 ± 137.7 mm2 in windsock vs 428.3 ± 158.9 ml in cauliflower, p = 0.021) and LAA volume (7.4 ± 3.0 mm2 in windsock vs 8.5 ± 4.8 mm2 in cauliflower, p = 0.012) in patients with windsock LAA morphology, whereas the LAA flow velocity did not differ significantly. Reduced LAA function and swan LAA morphology were independently associated with a higher prevalence of stroke/TIA, whereas the windsock LAA shape proved to be protective. Comparing the differences between the various LAA morphology types, significantly lower LAA volume and LAA orifice area were measured in the windsock LAA shape than in the cauliflower LAA shape.

Plasma lipidomics and coronary plaque changes: a substudy of the SMARTool clinical trial.

AIMS: To date, no studies have investigated the association between lipid species and coronary plaque changes over time, quantitatively assessed by serial imaging. We aimed to prospectively determine the association between lipid species quantified by a plasma lipidomic analysis and coronary plaque changes according to composition assessed by a quantitative serial analysis of coronary computed tomography angiography (CTA). METHODS AND RESULTS: Patients with suspected coronary artery disease (CAD) undergoing baseline coronary CTA were prospectively enrolled by seven EU centres in the SMARTool study and submitted to clinical, molecular, and coronary CTA re-evaluation at follow-up (an inter-scan period of 6.39 ± 1.17 years). Out of 202 patients who were analysed in the SMARTool main clinical study, a lipidomic analysis was performed in 154 patients before the baseline coronary CTA, and this group was included in the present study. A quantitative CTA analysis was performed by using a separate core laboratory blinded from clinical data. In the univariable analysis, it was found that no lipid species were significantly associated with annual total and calcified plaque changes. After adjusting for clinical variables at baseline and statin use, it was found that three lipid species were significantly associated with non-calcified plaque progression. In detail, cholesteryl ester(20:3), sphingomyelin (SM)(40:3), and SM(41:1) were found to be positively related to non-calcified plaque progression (Bonferroni-adjusted P-values = 0.005, 0.016, and 0.004, respectively). CONCLUSION: The current study showed an independent relationship between specific lipid species determined by a plasma lipidomic analysis and non-calcified coronary plaque progression assessed by a serial, quantitative coronary CTA analysis.

Lipoprotein(a) and Long-Term Plaque Progression, Low-Density Plaque, and Pericoronary Inflammation.

Importance: Lipoprotein(a) (Lp[a]) is a causal risk factor for cardiovascular disease; however, long-term effects on coronary atherosclerotic plaque phenotype, high-risk plaque formation, and pericoronary adipose tissue inflammation remain unknown. Objective: To investigate the association of Lp(a) levels with long-term coronary artery plaque progression, high-risk plaque, and pericoronary adipose tissue inflammation. Design, Setting, and Participants: This single-center prospective cohort study included 299 patients with suspected coronary artery disease (CAD) who underwent per-protocol repeated coronary computed tomography angiography (CCTA) imaging with an interscan interval of 10 years. Thirty-two patients were excluded because of coronary artery bypass grafting, resulting in a study population of 267 patients. Data for this study were collected from October 2008 to October 2022 and analyzed from March 2023 to March 2024. Exposures: The median scan interval was 10.2 years. Lp(a) was measured at follow-up using an isoform-insensitive assay. CCTA scans were analyzed with a previously validated artificial intelligence-based algorithm (atherosclerosis imaging-quantitative computed tomography). Main Outcome and Measures: The association between Lp(a) and change in percent plaque volumes was investigated in linear mixed-effects models adjusted for clinical risk factors. Secondary outcomes were presence of low-density plaque and presence of increased pericoronary adipose tissue attenuation at baseline and follow-up CCTA imaging. Results: The 267 included patients had a mean age of 57.1 (SD, 7.3) years and 153 were male (57%). Patients with Lp(a) levels of 125 nmol/L or higher had twice as high percent atheroma volume (6.9% vs 3.0%; P = .01) compared with patients with Lp(a) levels less than 125 nmol/L. Adjusted for other risk factors, every doubling of Lp(a) resulted in an additional 0.32% (95% CI, 0.04-0.60) increment in percent atheroma volume during the 10 years of follow-up. Every doubling of Lp(a) resulted in an odds ratio of 1.23 (95% CI, 1.00-1.51) and 1.21 (95% CI, 1.01-1.45) for the presence of low-density plaque at baseline and follow-up, respectively. Patients with higher Lp(a) levels had increased pericoronary adipose tissue attenuation around both the right coronary artery and left anterior descending at baseline and follow-up. Conclusions and Relevance: In this long-term prospective serial CCTA imaging study, higher Lp(a) levels were associated with increased progression of coronary plaque burden and increased presence of low-density noncalcified plaque and pericoronary adipose tissue inflammation. These data suggest an impact of elevated Lp(a) levels on coronary atherogenesis of high-risk, inflammatory, rupture-prone plaques over the long term.

Artificial intelligence coronary computed tomography, coronary computed tomography angiography using fractional flow reserve, and physician visual interpretation in the per-vessel prediction of abnormal invasive adenosine fractional flow reserve.

Aims: A comparison of diagnostic performance comparing AI-QCTISCHEMIA, coronary computed tomography angiography using fractional flow reserve (CT-FFR), and physician visual interpretation on the prediction of invasive adenosine FFR have not been evaluated. Furthermore, the coronary plaque characteristics impacting these tests have not been assessed. Methods and results: In a single centre, 43-month retrospective review of 442 patients referred for coronary computed tomography angiography and CT-FFR, 44 patients with CT-FFR had 54 vessels assessed using intracoronary adenosine FFR within 60 days. A comparison of the diagnostic performance among these three techniques for the prediction of FFR ≤ 0.80 was reported. The mean age of the study population was 65 years, 76.9% were male, and the median coronary artery calcium was 654. When analysing the per-vessel ischaemia prediction, AI-QCTISCHEMIA had greater specificity, positive predictive value (PPV), diagnostic accuracy, and area under the curve (AUC) vs. CT-FFR and physician visual interpretation CAD-RADS. The AUC for AI-QCTISCHEMIA was 0.91 vs. 0.76 for CT-FFR and 0.62 for CAD-RADS ≥ 3. Plaque characteristics that were different in false positive vs. true positive cases for AI-QCTISCHEMIA were max stenosis diameter % (54% vs. 67%, P < 0.01); for CT-FFR were maximum stenosis diameter % (40% vs. 65%, P < 0.001), total non-calcified plaque (9% vs. 13%, P < 0.01); and for physician visual interpretation CAD-RADS ≥ 3 were total non-calcified plaque (8% vs. 12%, P < 0.01), lumen volume (681 vs. 510 mm3, P = 0.02), maximum stenosis diameter % (40% vs. 62%, P < 0.001), total plaque (19% vs. 33%, P = 0.002), and total calcified plaque (11% vs. 22%, P = 0.003). Conclusion: Regarding per-vessel prediction of FFR ≤ 0.8, AI-QCTISCHEMIA revealed greater specificity, PPV, accuracy, and AUC vs. CT-FFR and physician visual interpretation CAD-RADS ≥ 3.

Development and Validation of a Quantitative Coronary CT Angiography Model for Diagnosis of Vessel-Specific Coronary Ischemia.

BACKGROUND: Noninvasive stress testing is commonly used for detection of coronary ischemia but possesses variable accuracy and may result in excessive health care costs. OBJECTIVES: This study aimed to derive and validate an artificial intelligence-guided quantitative coronary computed tomography angiography (AI-QCT) model for the diagnosis of coronary ischemia that integrates atherosclerosis and vascular morphology measures (AI-QCTISCHEMIA) and to evaluate its prognostic utility for major adverse cardiovascular events (MACE). METHODS: A post hoc analysis of the CREDENCE (Computed Tomographic Evaluation of Atherosclerotic Determinants of Myocardial Ischemia) and PACIFIC-1 (Comparison of Coronary Computed Tomography Angiography, Single Photon Emission Computed Tomography [SPECT], Positron Emission Tomography [PET], and Hybrid Imaging for Diagnosis of Ischemic Heart Disease Determined by Fractional Flow Reserve) studies was performed. In both studies, symptomatic patients with suspected stable coronary artery disease had prospectively undergone coronary computed tomography angiography (CTA), myocardial perfusion imaging (MPI), SPECT, or PET, fractional flow reserve by CT (FFRCT), and invasive coronary angiography in conjunction with invasive FFR measurements. The AI-QCTISCHEMIA model was developed in the derivation cohort of the CREDENCE study, and its diagnostic performance for coronary ischemia (FFR ≤0.80) was evaluated in the CREDENCE validation cohort and PACIFIC-1. Its prognostic value was investigated in PACIFIC-1. RESULTS: In CREDENCE validation (n = 305, age 64.4 ± 9.8 years, 210 [69%] male), the diagnostic performance by area under the receiver-operating characteristics curve (AUC) on per-patient level was 0.80 (95% CI: 0.75-0.85) for AI-QCTISCHEMIA, 0.69 (95% CI: 0.63-0.74; P < 0.001) for FFRCT, and 0.65 (95% CI: 0.59-0.71; P < 0.001) for MPI. In PACIFIC-1 (n = 208, age 58.1 ± 8.7 years, 132 [63%] male), the AUCs were 0.85 (95% CI: 0.79-0.91) for AI-QCTISCHEMIA, 0.78 (95% CI: 0.72-0.84; P = 0.037) for FFRCT, 0.89 (95% CI: 0.84-0.93; P = 0.262) for PET, and 0.72 (95% CI: 0.67-0.78; P < 0.001) for SPECT. Adjusted for clinical risk factors and coronary CTA-determined obstructive stenosis, a positive AI-QCTISCHEMIA test was associated with aHR: 7.6 (95% CI: 1.2-47.0; P = 0.030) for MACE. CONCLUSIONS: This newly developed coronary CTA-based ischemia model using coronary atherosclerosis and vascular morphology characteristics accurately diagnoses coronary ischemia by invasive FFR and provides robust prognostic utility for MACE beyond presence of stenosis.

Rationale and design of the CONFIRM2 (Quantitative COroNary CT Angiography Evaluation For Evaluation of Clinical Outcomes: An InteRnational, Multicenter Registry) study.

BACKGROUND: In the last 15 years, large registries and several randomized clinical trials have demonstrated the diagnostic and prognostic value of coronary computed tomography angiography (CCTA). Advances in CT scanner technology and developments of analytic tools now enable accurate quantification of coronary artery disease (CAD), including total coronary plaque volume and low attenuation plaque volume. The primary aim of CONFIRM2, (Quantitative COroNary CT Angiography Evaluation For Evaluation of Clinical Outcomes: An InteRnational, Multicenter Registry) is to perform comprehensive quantification of CCTA findings, including coronary, non-coronary cardiac, non-cardiac vascular, non-cardiac findings, and relate them to clinical variables and cardiovascular clinical outcomes. DESIGN: CONFIRM2 is a multicenter, international observational cohort study designed to evaluate multidimensional associations between quantitative phenotype of cardiovascular disease and future adverse clinical outcomes in subjects undergoing clinically indicated CCTA. The targeted population is heterogenous and includes patients undergoing CCTA for atherosclerotic evaluation, valvular heart disease, congenital heart disease or pre-procedural evaluation. Automated software will be utilized for quantification of coronary plaque, stenosis, vascular morphology and cardiac structures for rapid and reproducible tissue characterization. Up to 30,000 patients will be included from up to 50 international multi-continental clinical CCTA sites and followed for 3-4 years. SUMMARY: CONFIRM2 is one of the largest CCTA studies to establish the clinical value of a multiparametric approach to quantify the phenotype of cardiovascular disease by CCTA using automated imaging solutions.

Plaque volume, composition, and fraction versus ischemia and outcomes in patients with coronary artery disease.

BACKGROUND: The various plaque components have been associated with ischemia and outcomes in patients with coronary artery disease (CAD). The main goal of this analysis was to test the hypothesis that, at patient level, the fraction of non-calcified plaque volume (PV) of total PV is associated with ischemia and outcomes in patients with CAD. This ratio could be a simple and clinically useful parameter, if predicting outcomes. METHODS: Consecutive patients with suspected CAD undergoing coronary computed tomography angiography with selective positron emission tomography perfusion imaging were selected. Plaque components were quantitatively analyzed at patient level. The fraction of various plaque components were expressed as percentage of total PV and examined among patients with non-obstructive CAD, suspected stenosis with normal perfusion, and those with reduced myocardial perfusion. Clinical outcomes included all-cause mortality and myocardial infarction. RESULTS: In total, 494 patients (age 63 â€‹± â€‹9 years, 55% male) were included. Total PV and all plaque components were significantly larger in patients with reduced myocardial perfusion compared to patients with normal perfusion and those with non-obstructive CAD. During follow-up 35 events occurred. Patients with any plaque component â€‹≥ â€‹median showed worse outcomes (log-rank p â€‹< â€‹0.001 for all). In addition, low-attenuation plaque â€‹≥ â€‹median was associated with worse outcomes independent of total PV (adjusted HR: 2.754, 95% CI: 1.022-7.0419, p â€‹= â€‹0.045). The fractions of the various plaque components were not associated with outcomes. CONCLUSION: Larger total PV or any plaque component at patient level are associated with abnormal myocardial perfusion and adverse events. The various plaque components as fraction of total PV lack additional prognostic value.

Pericoronary Adipose Tissue Attenuation in Patients With Acute Coronary Syndrome Versus Stable Coronary Artery Disease.

BACKGROUND: Pericoronary adipose tissue (PCAT) attenuation has been associated with coronary inflammation and can be evaluated with coronary computed tomography angiography. The aims of this study were to compare the PCAT attenuation across precursors of culprit and nonculprit lesions of patients with acute coronary syndrome versus stable coronary artery disease (CAD). METHODS: In this case-control study, patients with suspected CAD who underwent coronary computed tomography angiography were included. Patients who developed an acute coronary syndrome within 2 years after the coronary computed tomography angiography scan were identified, and patients with stable CAD (defined as any coronary plaque ≥30% luminal diameter stenosis) were 1:2 propensity score matched for age, sex, and cardiac risk factors. The mean PCAT attenuation was analyzed at lesion level and compared between precursors of culprit lesions, nonculprit lesions, and stable coronary plaques. RESULTS: In total, 198 patients (age 62±10 years, 65% male) were selected, including 66 patients who developed an acute coronary syndrome and 132 propensity matched patients with stable CAD. Overall, 765 coronary lesions were analyzed (culprit lesion precursors: n=66; nonculprit lesion precursors: n=207; and stable lesions: n=492). Culprit lesion precursors had larger total plaque volume, fibro-fatty plaque volume, and low-attenuation plaque volume compared to nonculprit and stable lesions. The mean PCAT attenuation was significantly higher across culprit lesion precursors compared to nonculprit and stable lesions (-63.8±9.7 Hounsfield units versus -68.8±10.6 Hounsfield units versus -69.6±10.6 Hounsfield units, respectively; P<0.001), whereas the mean PCAT attenuation around nonculprit and stable lesions was not significantly different (P=0.99). CONCLUSIONS: The mean PCAT attenuation is significantly increased across culprit lesion precursors in patients with acute coronary syndrome, compared to nonculprit lesions of these patients and to lesions of patients with stable CAD, which may suggest a higher intensity of inflammation. PCAT attenuation on coronary computed tomography angiography may be a novel marker to identify high-risk plaques.

Importance of plaque volume and composition for the prediction of myocardial ischaemia using sequential coronary computed tomography angiography/positron emission tomography imaging.

AIMS: Coronary atherosclerosis with a large necrotic core has been postulated to reduce the vasodilatory capacity of vascular tissue. In the present analysis, we explored whether total plaque volume and necrotic core volume on coronary computed tomography angiography (CCTA) are independently associated with myocardial ischaemia on positron emission tomography (PET). METHODS AND RESULTS: From a registry of symptomatic patients with suspected coronary artery disease and clinically indicated CCTA with sequential [15O]H2O PET myocardial perfusion imaging, we quantitatively measured diameter stenosis, total and compositional plaque volumes on CCTA. Primary endpoint was myocardial ischaemia on PET, defined as an absolute stress myocardial blood flow ≤2.4 mL/g/min in ≥1 segment. Multivariable prediction models for myocardial ischaemia were consecutively created using logistic regression analysis (stenosis model: diameter stenosis ≥50%; plaque volume model: +total plaque volume; plaque composition model: +necrotic core volume). A total of 493 patients (mean age 63 ± 8 years, 54% men) underwent sequential CCTA/PET imaging. In 153 (31%) patients, myocardial ischaemia was detected on PET. Diameter stenosis ≥50% (P < 0.001) and necrotic core volume (P = 0.029) were independently associated with myocardial ischaemia, while total plaque volume showed borderline significance (P = 0.052). The plaque composition model (χ2 = 169) provided incremental value for the prediction of ischaemia when compared with the stenosis model (χ2 = 138, P < 0.001) and plaque volume model (χ2 = 164, P = 0.021). CONCLUSION: The volume of necrotic core on CCTA independently and incrementally predicts myocardial ischaemia on PET, beyond diameter stenosis alone.